Evidence map›Paper›PMID 40989079›Full record

ArticleInternational journal of reproductive biomedicine2025

Transcriptomic-based analysis of endometrial tissues from adenomyosis patients reveals significant inflammation biomarkers: A bioinformatics study.

Marni Sianturi, Alauddin Syaifulanwar, Darmawi Darmawi, Wirawan Adikusuma, Lalu Muhammad Irham, Muhammad Yusuf, Rifia Tiara Fani, Febriani Febriani

Abstract read
In one paragraph

Article in International journal of reproductive biomedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Marni SianturiMaster's Program in Biomedical Sciences, Faculty of Medicine, Universitas Riau, Pekanbaru, Indonesia.
Alauddin SyaifulanwarMaster's Program in Biomedical Sciences, Faculty of Medicine, Universitas Riau, Pekanbaru, Indonesia.
Darmawi DarmawiDepartment of Histology, Faculty of Medicine, Universitas Riau, Pekanbaru, Indonesia.
Wirawan AdikusumaDepartment of Pharmacy, Universitas Muhammadiyah Mataram, Mataram, Indonesia.
Lalu Muhammad IrhamDepartment of Pharmacology and Clinical Pharmacy, Universitas Ahmad Dahlan, Yogyakarta, Indonesia.
Muhammad YusufDepartment of Obstetrics and Gynecology, Faculty of Medicine, Universitas Riau, Pekanbaru, Indonesia.
Rifia Tiara FaniDepartment of Veterinary, Faculty of Medicine, Universitas Riau, Pekanbaru, Indonesia.
Febriani FebrianiDepartment of Obstetrics and Gynecology, Faculty of Medicine, Universitas Riau, Pekanbaru, Indonesia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Adenomyosis is a gynecological disorder characterized by the presence of endometrial tissue within the myometrium, with incidence rates ranging from 10-65% among women of reproductive age. Objective: This study utilized transcriptomic analysis to identify significant biomarkers associated with inflammation in endometrial tissue from patients with adenomyosis. Materials and Methods: In this bioinformatics study, we utilized publicly available transcriptomic datasets. The research involved the systematic analysis of RNA sequencing data obtained from the NCBI-GEO database. Using a high-throughput RNA sequencing database from GSE190580 and GSE157718, we compared gene expression profiles between endometrium tissues of adenomyosis patients and healthy controls. Subsequently, pathways implicated in adenomyosis were analyzed through the Kyoto Encyclopedia of Genes and Genomes and gene ontology. Results: Pathway analysis revealed the aberration of inflammation-related pathways, including tumor necrosis factor (TNF) and Ras-related protein 1 signaling. Furthermore, gene ontology analysis uncovered key biological processes, such as macrophage differentiation and extracellular matrix organization, which are central to the inflammatory response in adenomyosis. Candidate biomarkers, including transmembrane protein kinases, were identified as potential therapeutic targets. We found the top 5 genes that play a role in inflammation in adenomyosis, including TNF-α-induced protein 6, matrix metalloproteinase 7, TNF-α-induced protein 3, leukemia inhibitory factor, and serum and glucocorticoid-regulated kinase 1. Statistical significance was determined with adjusted p Conclusion: These findings enhance our understanding of the molecular mechanisms of adenomyosis and propose novel biomarkers for more effective diagnostic and therapeutic strategies.

Indexed as

AdenomyosisBioinformaticsBiomarkerInflammation.

Identifiers

PMID40989079
PMCPMC12413538

What Socratic holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.